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Proceedings Paper

Multi-site evaluation of a clinical decision support system for radiation therapy
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Paper Abstract

We have developed an imaging informatics based decision support system that learns from retrospective treatment plans to provide recommendations for healthy tissue sparing to prospective incoming patients. This system incorporates a model of best practices from previous cases, specific to tumor anatomy. Ultimately, our hope is to improve clinical workflow efficiency, patient outcomes and to increase clinician confidence in decision-making. The success of such a system depends greatly on the training dataset, which in this case, is the knowledge base that the data-mining algorithm employs. The size and heterogeneity of the database is essential for good performance. Since most institutions employ standard protocols and practices for treatment planning, the diversity of this database can be greatly increased by including data from different institutions. This work presents the results of incorporating cross-country, multi-institutional data into our decision support system for evaluation and testing.

Paper Details

Date Published: 25 March 2016
PDF: 7 pages
Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 97890E (25 March 2016); doi: 10.1117/12.2217733
Show Author Affiliations
Ruchi Deshpande, The Univ. of Southern California (United States)
John DeMarco, Univ. of California, Los Angeles (United States)
Kerstin Kessel, Technische Univ. München (Germany)
Brent J. Liu, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 9789:
Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations
Jianguo Zhang; Tessa S. Cook, Editor(s)

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